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CSV Singapore Department of Statistics

Resident Population by Place of Birth, Ethnic Group and Sex (Census of Population 2020)

Description

Understand birthplace composition among Singapore residents from the Census of Population 2020 by ethnic group and sex. The Singapore Department of Statistics release reports population counts for Chinese, Malay, Indian, and other groups, supporting migration history, diversity, and identity research in Singapore.

Official description

Source: SINGAPORE DEPARTMENT OF STATISTICS Data Last Updated: 16/06/2021 Update Frequency: 10 years Survey period: Census of Population 2020 Adapted from: https://tablebuilder.singstat.gov.sg/table/CT/17402

Download CSV View on data.gov.sg
Last updated
Rows
12
Columns
16

Chart

Values are summed where multiple rows share the same category.

Data

Number (Total) Total (Total) Males (Total) Females (Chinese) Total (Chinese) Males (Chinese) Females (Malays) Total (Malays) Males (Malays) Females (Indians) Total (Indians) Males (Indians) Females (Others) Total (Others) Males (Others) Females
Total 4044210.000000 1977556.000000 2066654.000000 3006769.000000 1461344.000000 1545425.000000 545498.000000 271332.000000 274166.000000 362274.000000 185565.000000 176709.000000 129669.000000 59315.000000 70354.000000
Singapore 3096630.000000 1570296.000000 1526334.000000 2323465.000000 1177958.000000 1145507.000000 512222.000000 260208.000000 252014.000000 216884.000000 110007.000000 106877.000000 44059.000000 22123.000000 21936.000000
Outside Singapore 947580.000000 407260.000000 540320.000000 683304.000000 283386.000000 399918.000000 33276.000000 11124.000000 22152.000000 145390.000000 75558.000000 69832.000000 85610.000000 37192.000000 48418.000000
Malaysia 459732.000000 197816.000000 261916.000000 415594.000000 178443.000000 237151.000000 20760.000000 7882.000000 12878.000000 21589.000000 10690.000000 10899.000000 1789.000000 801.000000 988.000000
Mainland China 169038.000000 64728.000000 104310.000000 168670.000000 64587.000000 104083.000000 6.000000 1.000000 5.000000 44.000000 25.000000 19.000000 318.000000 115.000000 203.000000
India 111865.000000 58824.000000 53041.000000 123.000000 54.000000 69.000000 18.000000 8.000000 10.000000 111371.000000 58582.000000 52789.000000 353.000000 180.000000 173.000000
Indonesia 56141.000000 18626.000000 37515.000000 43973.000000 15636.000000 28337.000000 11093.000000 2607.000000 8486.000000 626.000000 235.000000 391.000000 449.000000 148.000000 301.000000
Other Asian Countries / Regions 113662.000000 45752.000000 67910.000000 41495.000000 18335.000000 23160.000000 726.000000 342.000000 384.000000 8971.000000 4798.000000 4173.000000 62470.000000 22277.000000 40193.000000
Europe 17207.000000 11089.000000 6118.000000 3122.000000 1565.000000 1557.000000 119.000000 55.000000 64.000000 977.000000 449.000000 528.000000 12989.000000 9020.000000 3969.000000
USA and Canada 8788.000000 4643.000000 4145.000000 4780.000000 2224.000000 2556.000000 82.000000 44.000000 38.000000 807.000000 312.000000 495.000000 3119.000000 2063.000000 1056.000000
Australia and New Zealand 6009.000000 3180.000000 2829.000000 2781.000000 1268.000000 1513.000000 178.000000 78.000000 100.000000 433.000000 183.000000 250.000000 2617.000000 1651.000000 966.000000
Others 5138.000000 2602.000000 2536.000000 2766.000000 1274.000000 1492.000000 294.000000 107.000000 187.000000 572.000000 284.000000 288.000000 1506.000000 937.000000 569.000000

Columns

Column Type Categorical
Number Text No
(Total) Total Numeric No
(Total) Males Numeric No
(Total) Females Numeric No
(Chinese) Total Numeric No
(Chinese) Males Numeric No
(Chinese) Females Numeric No
(Malays) Total Numeric No
(Malays) Males Numeric No
(Malays) Females Numeric No
(Indians) Total Numeric No
(Indians) Males Numeric No
(Indians) Females Numeric No
(Others) Total Numeric No
(Others) Males Numeric No
(Others) Females Numeric No